Lead Machine Learning Engineer

hace 2 semanas

Argentina EPAM Systems A tiempo completo

We are in search of a Lead Machine Learning Engineer to direct the design, implementation, and optimization of ML-based systems that intelligently recommend user‑generated content, aiming to boost engagement. This role involves leading the development of robust machine learning pipelines and overseeing high‑performance deployments suited for real‑time data environments. Responsibilities Lead the design and execution of scalable, high‑performance machine learning pipelines for online and offline feature engineering Drive the development and tuning of advanced machine learning models, primarily utilizing Python and TensorFlow Optimize and manage the deployment of inference pipelines tailored for real‑time, low‑latency applications such as player telemetry Guide and standardize machine learning workflow management processes using MLflow across the team Supervise and expand data integration pipelines via ETL/ELT processes on Databricks Ensure reliability, debugging, and continuous performance tuning of production‑grade ML systems Establish scalable and automated methodologies for feature engineering and durable model deployments Collaborate effectively with senior stakeholders to align machine learning solutions with organizational objectives Strategize effective utilization of Databricks for efficient dataset management and computational workflows Set and uphold industry‑leading best practices for scalable, maintainable, and efficient ML systems Requirements 5+ years of experience building scalable machine learning pipelines and production‑grade workflows Minimum of 1 year of leadership experience in relevant roles Demonstrated expertise in Databricks, MLflow, and TensorFlow in professional applications Strong proficiency in Python for advanced machine learning and data engineering Solid background in ETL/ELT platforms with significant experience in large‑scale integration processes Deep familiarity with real‑time processing systems optimized for low latency Proven skills in designing and scaling workflows for both online and offline feature engineering Expertise in managing ML model lifecycles and optimizing pipelines Capability to deliver scalable, high‑performance solutions in multifaceted and evolving environments Excellent command of written and spoken English (B2+ level) Nice to have Comprehensive understanding of recommender systems with an emphasis on enhancing content discoverability and engagement Proficiency in deploying machine learning systems within AWS or comparable cloud infrastructure Background in real‑time analytics coupled with telemetry‑driven data solutions We offer International projects with top brands Work with global teams of highly skilled, diverse peers Employee financial programs Paid time off and sick leave Upskilling, reskilling and certification courses Unlimited access to the LinkedIn Learning library and 22,000+ courses Global career opportunities Volunteer and community involvement opportunities EPAM Employee Groups Award‑winning culture recognized by Glassdoor, Newsweek and LinkedIn #J-18808-Ljbffr

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